There is no statistical answer to what is a good r squared value. That is a professional judgement that depends on the phenomenon in question. In cases where a wide range of factors contribute to the dependent variable getting 10 percent R squared might be better than the norm. In other cases you can end up with very high r squared values (eighty or more percent). I would look for studies in the literature that addressed this and see what their r square values are. I am curious how you would know that ten percent would be random, have you seen other studies in this area?
When you have a lot of variables (and 38 is a huge number of variables to have in a regression) r squared is not ideal because it gets higher as the number of variables increases. You should use adjusted R squared which adjusts for this.
I have never encountered R squared predicted before.